Aspects relate to computer software, and more specifically, to a cloud independent tuning service for autonomously managed workloads.
Service level agreements (SLAs) may define the levels of service being sold by service providers, such as cloud computing providers. SLAs for workload performance in cloud or other virtualized hosting environments are typically static and specific to how that workload might consume resources on a certain operating platform in that hosting environment. These environment-specific SLAs may hamper workload portability across multiple platforms or hosting environments where resources vary greatly. Static SLAs may also increase the amount of work required to generate an SLA for a given workload, because the workload may need to be performance tested in each target platform to determine the correct parameters for the SLA. When a workload outgrows its SLA, the workload has no real-time communication mechanism to renegotiate its SLA with its hosting environment.
Workloads do not have the ability to dynamically span cloud providers. Furthermore, a workload in one cloud provider cannot start using resources or a workload clone in another cloud environment during times of peak usage. Workloads are further unable to easily migrate between different cloud providers, from public to private clouds, between public clouds, and the like. Furthermore, workloads are not able to self-manage their resources in a cloud provider independent manner when they are deployed in cloud providers that do not support self-managed workloads.